Improving the accuracy of Møller-Plesset perturbation theory with neural networks.
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Preface: Special Topic: From Quantum Mechanics to Force Fields.MoleculeNet: a benchmark for molecular machine learning.The TensorMol-0.1 model chemistry: a neural network augmented with long-range physics.Diagnostics of Data-Driven Models: Uncertainty Quantification of PM7 Semi-Empirical Quantum Chemical Method
P2860
Improving the accuracy of Møller-Plesset perturbation theory with neural networks.
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Improving the accuracy of Møller-Plesset perturbation theory with neural networks.
@en
Improving the accuracy of Møller-Plesset perturbation theory with neural networks.
@nl
type
label
Improving the accuracy of Møller-Plesset perturbation theory with neural networks.
@en
Improving the accuracy of Møller-Plesset perturbation theory with neural networks.
@nl
prefLabel
Improving the accuracy of Møller-Plesset perturbation theory with neural networks.
@en
Improving the accuracy of Møller-Plesset perturbation theory with neural networks.
@nl
P2093
P2860
P356
P1476
Improving the accuracy of Møller-Plesset perturbation theory with neural networks
@en
P2093
Alexander G Donchev
Cory Hargus
David E Shaw
Felipe Hernández
John L Klepeis
Ka-Hei Law
Karthik Siva
P2860
P304
P356
10.1063/1.4986081
P407
P577
2017-10-01T00:00:00Z